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Human resource management in the age of generative artificial intelligence: Perspectives and research directions on ChatGPT

Lookup NU author(s): Professor Savvas PapagiannidisORCiD

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).

Abstract

Abstract ChatGPT and its variants that use generative artificial intelligence (AI) models have rapidly become a focal point in academic and media discussions about their potential benefits and drawbacks across various sectors of the economy, democracy, society, and environment. It remains unclear whether these technologies result in job displacement or creation, or if they merely shift human labour by generating new, potentially trivial or practically irrelevant, information and decisions. According to the CEO of ChatGPT, the potential impact of this new family of AI technology could be as big as “the printing press”, with significant implications for employment, stakeholder relationships, business models, and academic research, and its full consequences are largely undiscovered and uncertain. The introduction of more advanced and potent generative AI tools in the AI market, following the launch of ChatGPT, has ramped up the “AI arms race”, creating continuing uncertainty for workers, expanding their business applications, while heightening risks related to well-being, bias, misinformation, context insensitivity, privacy issues, ethical dilemmas, and security. Given these developments, this perspectives editorial offers a collection of perspectives and research pathways to extend HRM scholarship in the realm of generative AI. In doing so, the discussion synthesizes the literature on AI and generative AI, connecting it to various aspects of HRM processes, practices, relationships, and outcomes, thereby contributing to shaping the future of HRM research.

Publication metadata

Author(s): Budhwar P, Chowdhury S, Wood G, Aguinis H, Bamber GJ, Beltran JR, Boselie P, Lee Cooke F, Decker S, DeNisi A, Dey PK, Guest D, Knoblich AJ, Malik A, Paauwe J, Papagiannidis S, Patel C, Pereira V, Ren S, Rogelberg S, Saunders MNK, Tung RL, Varma A

Publication type: Article

Publication status: Published

Journal: Human Resource Management Journal

Year: 2023

Volume: 33

Issue: 3

Pages: 606–659

Online publication date: 10/07/2023

Acceptance date: 09/06/2023

Date deposited: 14/07/2023

ISSN (print): 0954-5395

ISSN (electronic): 1748-8583

Publisher: Wiley-Blackwell Publishing Ltd.

URL: https://doi.org/10.1111/1748-8583.12524

DOI: 10.1111/1748-8583.12524

ePrints DOI: 10.57711/q84k-cs77

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